PSO–FWA: A New Hybrid Algorithm for Solving Nonlinear Equation Systems

Abstract

Nature-inspired optimization algorithms have been proposed for solving hard optimization problems, including the optimization-based solution of difficult systems of nonlinear equations. While there is no perfect optimization algorithm, the hybridization of such metaheuristic optimization algorithms has produced positive results by enhancing their capabilities and reducing their weaknesses. This paper presents a novel hybridization of Particle Swarm Optimization and the Fireworks Algorithm for solving nonlinear equation systems. The experimental results obtained indicate that the proposed hybrid algorithm outperforms both Particle Swarm Optimization and the Fireworks Algorithm, as well as a previously developed hybridization of these algorithms.